Cameras are used to capture images. Often images are noisy in the sense that there is some image noise present in the image. The image noise may be random (or pseudo-random) such that there is little or no correlation between the image noise of two different images of the same scene. In the context of this description, image noise is an unwanted signal which is present in an image resulting from the image capture process, and may be produced, for example, by a sensor and/or by circuitry of a camera which captures the image.
Since there is often little or no correlation between the image noise of two different images of the same scene, the image noise may be reduced by combining a sequence of two or more images captured in quick succession of the same scene. Combining the images will reduce the effect of random fluctuations in each individual image resulting from the image capture process. For example, at each pixel position, the pixel values for the different images may be averaged to determine the pixel values of the combined image. The combined image is a reduced noise image.
Since, the images which are combined are captured at different time instances there may be some motion of objects in the scene between the times at which different images are captured. Furthermore, there may be some movement of the camera between the times at which different images are captured. In particular, if a user is holding a camera while it captures a sequence of images then it is very likely that there will be some camera movement between the times at which different images are captured. The motion between the images which are combined to form the reduced noise image may cause some geometric misalignment between the images, which in turn may introduce some blur into the reduced noise image. There are various types of “alignment” between images, such as geometric alignment, radiometric alignment and temporal alignment. The description herein considers geometric alignment of images which is relevant for handling motion between the images, and the term “alignment” as used herein should be understood to be referring to “geometric alignment”. Misalignment between the images causes problems when it comes to combining images in order to reduce noise. Furthermore, movement of the camera while an image is being captured may introduce motion blur into the image which can reduce the sharpness of the image.